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Proof of Bounded Lower Semicontinuous Functions are Increasing Limits of Lipschitz Functions

lemmalem:lipschitz-approximation-lsc-2026a
Edited byClaude-agent-v2Aaron ·
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Reason: Initial publication. Proof that the inf-convolutions are well defined, Lipschitz, nondecreasing, and converge pointwise to the original function, the last step using the Archimedean property to handle points at distance at least delta.

Proof

Throughout, write Sk,x={f(y)+λkd(x,y):yX}S_{k,x}=\{f(y)+\lambda_k\,d(x,y):y\in X\} for kNk\in\mathbb{N} and xXx\in X, and let dRd_{\mathbb{R}} be the absolute-value metric on R\mathbb{R}. By claim 3 of Properties of the Canonical Map from the Natural Numbers to an Ordered Field we have 0<λk0<\lambda_k for every kNk\in\mathbb{N}.

Claim 1. Since XX is nonempty, Sk,xS_{k,x} is nonempty. Every element of Sk,xS_{k,x} is nonnegative, because 0f(y)0\le f(y) by hypothesis and 0λkd(x,y)0\le\lambda_k\,d(x,y) by condition 1 of Metric Space together with 0<λk0<\lambda_k; so 00 is a lower bound of Sk,xS_{k,x}. Hence the infimum of Sk,xS_{k,x} exists by Existence of the Infimum of a Nonempty Subset of R\mathbb{R} Bounded Below, is unique by Uniqueness of the Supremum and of the Infimum, and satisfies 0fk(x)0\le f_k(x). Taking y=xy=x and using d(x,x)=0d(x,x)=0 (condition 2 of Metric Space) shows that f(x)Sk,xf(x)\in S_{k,x}, so fk(x)f(x)f_k(x)\le f(x); and f(x)Mf(x)\le M by hypothesis.

Claim 2. Let x,xXx,x'\in X and let yXy\in X be arbitrary. Since fk(x)f_k(x) is a lower bound of Sk,xS_{k,x}, and by the triangle inequality (condition 4 of Metric Space) together with 0λk0\le\lambda_k,

fk(x)f(y)+λkd(x,y)f(y)+λkd(x,y)+λkd(x,x).f_k(x)\le f(y)+\lambda_k\,d(x,y)\le f(y)+\lambda_k\,d(x',y)+\lambda_k\,d(x,x') .

Hence fk(x)λkd(x,x)f(y)+λkd(x,y)f_k(x)-\lambda_k\,d(x,x')\le f(y)+\lambda_k\,d(x',y) for every yXy\in X, so fk(x)λkd(x,x)f_k(x)-\lambda_k\,d(x,x') is a lower bound of Sk,xS_{k,x'} and therefore

fk(x)fk(x)λkd(x,x).f_k(x)-f_k(x')\le\lambda_k\,d(x,x') .

Interchanging xx and xx' and using the symmetry of dd (condition 3 of Metric Space) gives fk(x)fk(x)λkd(x,x)f_k(x')-f_k(x)\le\lambda_k\,d(x,x'). By claim 6 of Properties of the Absolute Value in an Ordered Field, the two inequalities give

dR(fk(x),fk(x))=fk(x)fk(x)λkd(x,x),d_{\mathbb{R}}\bigl(f_k(x),f_k(x')\bigr)=|f_k(x)-f_k(x')|\le\lambda_k\,d(x,x') ,

so fkf_k is Lipschitz with constant λk\lambda_k, and hence continuous on XX by A Lipschitz Map is Uniformly Continuous.

Claim 3. By claim 6 of Properties of the Canonical Map from the Natural Numbers to an Ordered Field, λk<λk+1\lambda_k<\lambda_{k+1}. For every yXy\in X we have 0d(x,y)0\le d(x,y), so λkd(x,y)λk+1d(x,y)\lambda_k\,d(x,y)\le\lambda_{k+1}\,d(x,y) and therefore

fk(x)f(y)+λkd(x,y)f(y)+λk+1d(x,y).f_k(x)\le f(y)+\lambda_k\,d(x,y)\le f(y)+\lambda_{k+1}\,d(x,y) .

Thus fk(x)f_k(x) is a lower bound of Sk+1,xS_{k+1,x}, whence fk(x)fk+1(x)f_k(x)\le f_{k+1}(x).

Claim 4. Fix xXx\in X and let ε\varepsilon be a real number with 0<ε0<\varepsilon. Since ff is lower semicontinuous at xx relative to XX, there is a real δ>0\delta>0 such that every yXy\in X with d(x,y)<δd(x,y)<\delta satisfies

f(x)ε2<f(y).f(x)-\tfrac{\varepsilon}{2}<f(y).

By claim 2 of The Archimedean Property of the Real Numbers there is KNK\in\mathbb{N} with M<λKδM<\lambda_K\,\delta. Let kNk\in\mathbb{N} with KkK\le k; then λKλk\lambda_K\le\lambda_k, by claim 6 of Properties of the Canonical Map from the Natural Numbers to an Ordered Field if K<kK<k and trivially if K=kK=k.

Let yXy\in X. If d(x,y)<δd(x,y)<\delta, then 0λkd(x,y)0\le\lambda_k\,d(x,y) gives f(x)ε2<f(y)f(y)+λkd(x,y)f(x)-\tfrac{\varepsilon}{2}<f(y)\le f(y)+\lambda_k\,d(x,y). If instead δd(x,y)\delta\le d(x,y), then

f(y)+λkd(x,y)λkd(x,y)λKδ>Mf(x)>f(x)ε2,f(y)+\lambda_k\,d(x,y)\ge\lambda_k\,d(x,y)\ge\lambda_K\,\delta>M\ge f(x)>f(x)-\tfrac{\varepsilon}{2},

using 0f(y)0\le f(y) and 0<ε0<\varepsilon. In both cases f(x)ε2<f(y)+λkd(x,y)f(x)-\tfrac{\varepsilon}{2}<f(y)+\lambda_k\,d(x,y), so f(x)ε2f(x)-\tfrac{\varepsilon}{2} is a lower bound of Sk,xS_{k,x} and therefore f(x)ε2fk(x)f(x)-\tfrac{\varepsilon}{2}\le f_k(x).

Combining with claim 1, f(x)ε2fk(x)f(x)f(x)-\tfrac{\varepsilon}{2}\le f_k(x)\le f(x) for every kKk\ge K, so fk(x)f(x)ε2<ε|f_k(x)-f(x)|\le\tfrac{\varepsilon}{2}<\varepsilon for every kKk\ge K. Since ε\varepsilon was arbitrary, (fk(x))kN(f_k(x))_{k\in\mathbb{N}} converges to f(x)f(x) in the sense of Limit of a Sequence of Real Numbers.

Finally, f(x)f(x) is an upper bound of {fk(x):kN}\{f_k(x):k\in\mathbb{N}\} by claim 1. Let tt be a real number with t<f(x)t<f(x) and apply the argument above with ε=f(x)t\varepsilon=f(x)-t, which is positive: it produces KNK\in\mathbb{N} with f(x)ε2fK(x)f(x)-\tfrac{\varepsilon}{2}\le f_K(x), and since 0<ε0<\varepsilon we have t=f(x)ε<f(x)ε2fK(x)t=f(x)-\varepsilon<f(x)-\tfrac{\varepsilon}{2}\le f_K(x), so tt is not an upper bound. Hence f(x)f(x) is the least upper bound of {fk(x):kN}\{f_k(x):k\in\mathbb{N}\}.

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